There is an increasing need to provide indoor localization that replicates the outdoor localization provided by vehicle navigation systems, such as global positioning systems (GPS), in indoor environments where GPS signals are not typically able to register. Approaches for providing indoor localization include Radio Frequency (RF) fingerprinting, where WiFi or cellular signal measurements are matched against RF maps of a site of interest to infer a user's current location at the site, and vision-based Simultaneous Localization and Mapping (SLAM), where a map of an unknown environment is incrementally built by projected images and the viewer's current location and trajectory are deduced along the process. However, these indoor localization systems typically lack accuracy in localization in 3D space or require too resource-intensive computations and/or specialized hardware.